Background: Melanoma is a highly aggressive skin cancer with poor prognosis once metastasis occurs. Identifying metastasis-suppressive biomarkers is crucial for improving clinical outcomes. Materials and methods: We integrated three GEO da-tasets (GSE65904, GSE59455, GSE8401) to identify differentially expressed genes (DEGs) between metastatic and primary melanoma tissues. GO/KEGG enrichment, PPI network construction, and hub gene analysis were performed using STRING, Cytoscape (MCODE, CytoHubba), and Venn analysis. Clinical significance was val-idated via GEPIA and OSdream platforms. Results: We identified 37 overlapping DEGs enriched in keratinocyte differentiation and epithelial barrier functions. loric-rin (LOR), Keratin 6B (KRT6B), and filaggrin (FLG) were consistently downregu-lated in melanoma and identified as hub genes. Among them, LOR expression corre-lated with longer metastasis-free survival (p = 0.0466) and was negatively associated with ADAM12, ITGA4, and CDK1 expression in melanoma. These results suggest that LOR may suppress melanoma metastasis. Conclusion: LOR is a potential bi-omarker for predicting melanoma metastasis and progression, highlighting its value for prognosis and therapeutic targeting.